Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building (Block MD1), 12 Science Drive 2, #09-01v, Singapore, 117549, Singapore.
Policy, Research and Surveillance Division, Health Promotion Board, Singapore, Singapore.
Sci Rep. 2021 May 5;11(1):9633. doi: 10.1038/s41598-021-89141-3.
Daily step count is a readily accessible physical activity measure inversely related to many important health outcomes. However, its day-to-day variability is not clear, especially when measured by recent mobile devices. This study investigates number of measurement days required to reliably estimate the weekly and monthly levels of daily step count in adults using wrist-worn fitness trackers and smartphones. Data were from a 5-month physical activity program in Singapore. The 5-month period was divided into 22 weekly and 5 monthly time windows. For each time window, we leveraged data sampling procedures and estimated the minimum number of measurement days needed to achieve reliable mean daily step count with intraclass correlation coefficients (ICC) above 80%. The ICCs were derived using linear mixed effect models. We examined both simple random and random consecutive measurement days and conducted subgroup analysis by participant characteristics and tracking devices. Analysis of weekly and monthly step count included 212,048 and 112,865 adults, respectively. Fewer simple random measurement days are needed than random consecutive days for weekly time windows (mean 2.5, SD 0.5 vs mean 2.7, SD 0.5; p-value = 0.025). Similarly, monthly time windows require fewer measurements of simple random days than random consecutive days (mean 3.4, SD 0.5 vs mean 4.4, SD 0.5; p-value = 0.025). Younger participants and those tracking steps via smartphones consistently required more days. Being obese was associated with more measurement days for weekly time windows. In sum, to obtain reliable daily step count level, we recommend at least 3 measurement days for weekly and 5 days for monthly time window in adults. Fewer days could be considered for adults age 60+ years, while more days are required when tracking daily step via smartphones.
日常步数是一种易于获取的身体活动测量指标,与许多重要的健康结果呈负相关。然而,其日常变化尚不清楚,尤其是使用最近的移动设备进行测量时。本研究旨在调查使用腕戴式健身追踪器和智能手机可靠估计成年人每周和每月日常步数水平所需的测量天数。数据来自新加坡为期 5 个月的体力活动计划。5 个月的时间被分为 22 个每周和 5 个每月的时间窗口。对于每个时间窗口,我们利用数据采样程序,并使用线性混合效应模型来估计实现可靠平均日常步数(组内相关系数(ICC)大于 80%)所需的最小测量天数。我们分别检查了简单随机和随机连续测量日,并根据参与者特征和追踪设备进行了亚组分析。每周和每月步数分析分别纳入了 212,048 名和 112,865 名成年人。每周时间窗口需要的简单随机测量天数少于随机连续测量天数(平均 2.5,SD 0.5 与平均 2.7,SD 0.5;p 值=0.025)。类似地,每月时间窗口需要的简单随机测量天数少于随机连续测量天数(平均 3.4,SD 0.5 与平均 4.4,SD 0.5;p 值=0.025)。年轻参与者和通过智能手机追踪步数的参与者需要更多的天数。肥胖与每周时间窗口的更多测量天数相关。总之,为了获得可靠的日常步数水平,我们建议成年人每周至少进行 3 天测量,每月至少进行 5 天测量。对于 60 岁以上的成年人,可以考虑减少天数,而通过智能手机追踪日常步数则需要更多的天数。